Bibliographic record
Abstract
Abstract Hypothetical bias is tested based on inter‐ and intra‐respondent comparisons of choice behavior, applying a hypothetical and real choice experiment. The inter‐respondent comparison commonly applied in the environmental and agricultural economics literature consists of a control group of buyers who are asked to hypothetically choose between conventional and organic beans and an experimental group of buyers who are endowed to purchase the same beans using an identical experimental design. Hypothetical bias is tested by comparing inter‐ and intra‐respondents’ (i) hypothetical and real choices, (ii) preference parameters of the estimated choice models related to hypothetical and real choices, and (iii) hypothetical and real willingness to pay (WTP). Choices in the experimental group are highly consistent when switching from hypothetical to real choices for this study's homegrown goods. However, after being endowed, the price sensitivity of lower income households drops, suggesting a house money effect. WTP derived from actual purchases is higher than WTP based on hypothetical choices, indicating a negative hypothetical bias, but differences are only significant in the case of the inter‐respondent comparison. Actual prices paid by respondents in the field experiment appear to be considerably lower than the estimated WTP values and yield a mixed picture of hypothetical bias.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.067 | 0.192 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".